ACR System Workload Management via Segmented Content Identification
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Solution Overview
Problem
Current television systems lack the ability to accurately identify the content being viewed in real-time, limiting their capacity to provide contextually relevant information and interactive opportunities, and are inefficient in utilizing system resources for non-time-sensitive tasks.
Innovation Solution
The system identifies video segments by sampling pixel or audio data and matching it with a content database, allowing for contextually targeted content delivery and efficient resource management by processing data in real-time and non-real-time periods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system processes all content identification tasks in real-time, then content identification accuracy is improved, but system resource consumption increases
Solution Approach 1:
The patent segments content identification tasks into real-time and non-real-time categories. Real-time identification handles time-sensitive content delivery tasks, while non-real-time identification processes less time-critical tasks during off-peak hours. This segmentation allows the system to maintain identification accuracy for critical functions while reducing overall resource consumption by deferri
2Adaptability or versatility
If the system maintains a large content database for comprehensive content identification, then content coverage is improved, but system complexity increases
Solution Approach 1:
The patent divides the content database into real-time and non-real-time segments. The real-time database contains content requiring immediate identification, while the non-real-time database stores content for later processing. This segmentation reduces the complexity of real-time operations while maintaining comprehensive content coverage across both databases.
Solution Approach 2:
The system performs preliminary processing and indexing of content data during non-real-time periods when system resources are more available. This preliminary action prepares data structures and metadata in advance, reducing the complexity of real-time content identification operations while maintaining comprehensive content coverage.
3Speed
If the system processes content identification during peak hours, then response time is improved, but resource efficiency deteriorates
Solution Approach 1:
The patent segments processing tasks by time sensitivity and schedules them appropriately. Time-critical content identification tasks are processed during peak hours to ensure fast response times, while non-time-critical tasks are scheduled during off-peak hours to maximize resource efficiency. This temporal segmentation optimizes both response time and resource utilization.
Solution Approach 2:
The system implements periodic batch processing during off-peak hours to handle non-real-time content identification tasks. This periodic action allows the system to efficiently utilize resources during low-demand periods while maintaining real-time processing capabilities during peak hours, thereby optimizing overall resource efficiency without compromising critical response times.
Data Source
AI summary
Systems and methods include optimizing resource utilization of an automated content recognition (ACR) system by delaying the identification of certain large quantities of media cue data. The delayed identification of the media may be for the purpose of, for example, generating usage statistics or other non-time critical work flow, among other non-real-time uses. In addition, real-time identification of a certain subset of media cue data is performed for the purposes of video program substitution, interactive television opportunities or other time-specific events.